Determination of Precipitation Return Values in Complex Terrain and Their Evaluation

Abstract To determine return values at various return periods for extreme daily precipitation events over complex orography, an appropriate threshold value and distribution function are required. The return values are calculated using the peak-over-threshold approach in which only a reduced sample of precipitation events exceeding a predefined threshold is analyzed. To fit the distribution function to the sample, the L-moment method is used. It is found that the deviation between the fitted return values and the plotting positions of the ranked precipitation events is smaller for the kappa distribution than for the generalized Pareto distribution. As a second focus, the ability of regional climate models to realistically simulate extreme daily precipitation events is assessed. For this purpose the return values are derived using precipitation events exceeding the 90th percentile of the precipitation time series and a fit of a kappa distribution. The results of climate simulations with two different regional climate models are analyzed for the 30-yr period 1971–2000: the so-called consortium runs performed with the climate version of the Lokal Modell (referred to as the CLM-CR) at 18-km resolution and the Regional Model (REMO)–Umweltbundesamt (UBA) simulations at 10-km resolution. It was found that generally the return values are overestimated by both models. Averaged across the region the overestimation is higher for REMO–UBA compared to CLM-CR.

Download Full-text

Spatial extent of precipitation events: when big is getting bigger

Climate Dynamics ◽

10.1007/s00382-021-05998-0 ◽

2021 ◽

Author(s):

Dominic Matte ◽

Jens H. Christensen ◽

Tugba Ozturk

Keyword(s):

Global Warming ◽

Climate Models ◽

Daily Precipitation ◽

Regional Climate ◽

Regional Climate Models ◽

Grid Resolution ◽

Spatial Extent ◽

Precipitation Events ◽

Selection Of

AbstractUsing a sub-selection of regional climate models at 0.11° ($$\approx$$ ≈ 12 km) grid resolution from the EURO-CORDEX ensemble, we investigate how the spatial extent of areas associated with the most intensive daily precipitation events changes as a consequence of global warming. We address this by analysing three different warming levels: 1 °C, 2 °C and 3 °C. We find that not only does the intensity of such events increase, but their size will also change as a function of the warming: larger systems becomes more frequent and larger, while systems of lesser extent are reduced in numbers.

Download Full-text

Assessment of extreme wind speeds from Regional Climate Models – Part 1: Estimation of return values and their evaluation

Natural Hazards and Earth System Science ◽

10.5194/nhess-10-907-2010 ◽

2010 ◽

Vol 10 (4) ◽

pp. 907-922 ◽

Cited By ~ 43

Author(s):

M. Kunz ◽

S. Mohr ◽

M. Rauthe ◽

R. Lux ◽

Ch. Kottmeier

Keyword(s):

Distribution Function ◽

Climate Models ◽

Regional Climate ◽

Generalized Pareto Distribution ◽

Regional Climate Models ◽

Extreme Value Statistics ◽

Threshold Method ◽

Wind Speeds ◽

Extreme Wind ◽

Extreme Wind Speeds

Abstract. Frequency and intensity of gust wind speeds associated with severe mid-latitude winter storms are estimated by applying extreme value statistics to data sets from regional climate models (RCM). Maximum wind speeds related to probability are calculated with the classical peaks over threshold method, where a statistical distribution function is fitted to the reduced sample describing the tail of the distribution function. From different sensitivity studies it is found that the Generalized Pareto Distribution in combination with a Maximum-Likelihood estimator provide the most reliable and robust results. For a reference period from 1971 to 2000, the ability of the RCMs to realistically simulate extreme wind speeds is investigated. For this purpose, data from three RCM scenarios, including the REMO-UBA simulations at 10 km resolution and the so-called consortial runs performed with the CCLM at 18 km resolution (two runs), are evaluated with observations and a pre-existing storm hazard map for Germany. It is found that all RCMs tend to underestimate the magnitude of the gusts in a range between 10 and 30% for a 10-year return period. Averaged over the investigation area, the underestimation is higher for CCLM compared to REMO. The spatial distribution of the gusts, on the other hand, is well reproduced, in particular by REMO.

Download Full-text

Evaluation of uncertainties in mean and extreme precipitation under climate change for northwestern Mediterranean watersheds from high-resolution Med and Euro-CORDEX ensembles

Hydrology and Earth System Sciences ◽

10.5194/hess-22-673-2018 ◽

2018 ◽

Vol 22 (1) ◽

pp. 673-687 ◽

Cited By ~ 10

Author(s):

Antoine Colmet-Daage ◽

Emilia Sanchez-Gomez ◽

Sophie Ricci ◽

Cécile Llovel ◽

Valérie Borrell Estupina ◽

...

Keyword(s):

Climate Change ◽

High Resolution ◽

Extreme Precipitation ◽

Climate Models ◽

Regional Climate ◽

Regional Climate Models ◽

Historical Period ◽

Mountainous Regions ◽

Extreme Precipitation Events ◽

Precipitation Events

Abstract. The climate change impact on mean and extreme precipitation events in the northern Mediterranean region is assessed using high-resolution EuroCORDEX and MedCORDEX simulations. The focus is made on three regions, Lez and Aude located in France, and Muga located in northeastern Spain, and eight pairs of global and regional climate models are analyzed with respect to the SAFRAN product. First the model skills are evaluated in terms of bias for the precipitation annual cycle over historical period. Then future changes in extreme precipitation, under two emission scenarios, are estimated through the computation of past/future change coefficients of quantile-ranked model precipitation outputs. Over the 1981–2010 period, the cumulative precipitation is overestimated for most models over the mountainous regions and underestimated over the coastal regions in autumn and higher-order quantile. The ensemble mean and the spread for future period remain unchanged under RCP4.5 scenario and decrease under RCP8.5 scenario. Extreme precipitation events are intensified over the three catchments with a smaller ensemble spread under RCP8.5 revealing more evident changes, especially in the later part of the 21st century.

Download Full-text

Influence of Bias Correction Methods on Simulated Köppen−Geiger Climate Zones in Europe

Climate ◽

10.3390/cli7020018 ◽

2019 ◽

Vol 7 (2) ◽

pp. 18 ◽

Cited By ~ 3

Author(s):

Beáta Szabó-Takács ◽

Aleš Farda ◽

Petr Skalák ◽

Jan Meitner

Keyword(s):

Bias Correction ◽

Climate Models ◽

Regional Climate ◽

Generalized Pareto Distribution ◽

Regional Climate Models ◽

Climate Classification ◽

Quantile Mapping ◽

Temperature Bias ◽

Simulated Precipitation ◽

Precipitation And Temperature

Our goal was to investigate the influence of bias correction methods on climate simulations over the European domain. We calculated the Köppen−Geiger climate classification using five individual regional climate models (RCM) of the ENSEMBLES project in the European domain during the period 1961−1990. The simulated precipitation and temperature data were corrected using the European daily high-resolution gridded dataset (E-OBS) observed data by five methods: (i) the empirical quantile mapping of precipitation and temperature, (ii) the quantile mapping of precipitation and temperature based on gamma and Generalized Pareto Distribution of precipitation, (iii) local intensity scaling, (iv) the power transformation of precipitation and (v) the variance scaling of temperature bias corrections. The individual bias correction methods had a significant effect on the climate classification, but the degree of this effect varied among the RCMs. Our results on the performance of bias correction differ from previous results described in the literature where these corrections were implemented over river catchments. We conclude that the effect of bias correction may depend on the region of model domain. These results suggest that distribution free bias correction approaches are the most suitable for large domain sizes such as the pan-European domain.

Download Full-text

SA-OBS: A Daily Gridded Surface Temperature and Precipitation Dataset for Southeast Asia

Journal of Climate ◽

10.1175/jcli-d-16-0575.1 ◽

2017 ◽

Vol 30 (14) ◽

pp. 5151-5165 ◽

Cited By ~ 15

Author(s):

Else J. M. van den Besselaar ◽

Gerard van der Schrier ◽

Richard C. Cornes ◽

Aris Suwondo Iqbal ◽

Albert M. G. Klein Tank

Keyword(s):

Southeast Asia ◽

Climate Models ◽

Regional Climate ◽

Regional Climate Models ◽

Maximum Temperature ◽

Climate Assessment ◽

Temperature And Precipitation ◽

Interpolation Technique ◽

Precipitation Events ◽

Best Estimates

This study introduces a new daily high-resolution land-only observational gridded dataset, called SA-OBS, for precipitation and minimum, mean, and maximum temperature covering Southeast Asia. This dataset improves upon existing observational products in terms of the number of contributing stations, in the use of an interpolation technique appropriate for daily climate observations, and in making estimates of the uncertainty of the gridded data. The dataset is delivered on a 0.25° × 0.25° and a 0.5° × 0.5° regular latitude–longitude grid for the period 1981–2014. The dataset aims to provide best estimates of grid square averages rather than point values to enable direct comparisons with regional climate models. Next to the best estimates, daily uncertainties are quantified. The underlying daily station time series are collected in cooperation between meteorological services in the region: the Southeast Asian Climate Assessment and Dataset (SACA&D). Comparisons are made with station observations and other gridded station or satellite-based datasets (APHRODITE, CMORPH, TRMM). The comparisons show that vast differences exist in the average daily precipitation, the number of rainy days, and the average precipitation on a wet day between these datasets. SA-OBS closely resembles the station observations in terms of dry/wet frequency, the timing of precipitation events, and the reproduction of extreme precipitation. New versions of SA-OBS will be released when the station network in SACA&D has grown further.

Download Full-text

Applying the new spatially distributed Added Value Index and Climate Change Downscaling Signal for Regional Climate Models to high-resolution EURO-CORDEX and convection permitting scale simulations

10.5194/egusphere-egu21-8849 ◽

2021 ◽

Author(s):

James Ciarlo ◽

Erika Coppola ◽

Emanuela Pichelli ◽

Jose Abraham Torres Alavez ◽

Keyword(s):

Climate Change ◽

High Resolution ◽

General Circulation ◽

Climate Models ◽

Daily Precipitation ◽

Regional Climate ◽

Regional Climate Models ◽

General Circulation Models ◽

Added Value ◽

Spatially Distributed

Downscaling data from General Circulation Models (GCMs) with Regional Climate Models (RCMs) is a computationally expensive process, even more so running at the convection permitting scale (CP). Despite the high-resolution products of these simulations, the Added Value (AV) of these runs compared to their driving models is an important factor for consideration. A new method was recently developed to quantify the AV of historical simulations as well as the Climate Change Downscaling Signal (CCDS) of forecast runs. This method presents these quantities spatially and thus the specific regions with the most AV can be identified and understood.An analysis of daily precipitation from a 55-model EURO-CORDEX ensemble (at 12 km resolution) was assessed using this method. It revealed positive AV throughout the domain with greater emphasis in regions of complex topography, coast-lines, and the tropics. Similar CCDS was obtained when assessing the RCP 8.5 far future runs in these domains. This paper looks more closely at the CCDS obtained with this method and compares it to other climate change signals described in other studies.The same method is now being applied to assess the AV and CCDS of daily precipitation from an ensemble of models at the CP scale (~3 km) over different domains within Europe. The current stage of the analysis is also looking into the AV of using hourly precipitation instead of daily.

Download Full-text

Comparison of Characteristics and Spatial Distribution Tendency of Daily Precipitation based on the Regional Climate Models for the Korean Peninsula

Korean Society of Hazard Mitigation ◽

10.9798/kosham.2015.15.4.59 ◽

2015 ◽

Vol 15 (4) ◽

pp. 59-70

Author(s):

Jungho Kim ◽

Moojong Park ◽

Jingul Joo

Keyword(s):

Spatial Distribution ◽

Korean Peninsula ◽

Climate Models ◽

Daily Precipitation ◽

Regional Climate ◽

Regional Climate Models

Download Full-text

Regional, Very Heavy Daily Precipitation in NARCCAP Simulations

Journal of Hydrometeorology ◽

10.1175/jhm-d-12-068.1 ◽

2013 ◽

Vol 14 (4) ◽

pp. 1212-1227 ◽

Cited By ~ 18

Author(s):

Sho Kawazoe ◽

William J. Gutowski

Keyword(s):

Mississippi River ◽

Climate Models ◽

Climate Model ◽

Daily Precipitation ◽

Global Climate ◽

Global Climate Model ◽

Regional Climate ◽

Heavy Precipitation ◽

River Region ◽

Precipitation Events

Abstract The authors analyze the ability of the North American Regional Climate Change Assessment Program's ensemble of climate models to simulate very heavy daily precipitation and its supporting processes, comparing simulations that used observation-based boundary conditions with observations. The analysis includes regional climate models and a time-slice global climate model that all used approximately half-degree resolution. Analysis focuses on an upper Mississippi River region for winter (December–February), when it is assumed that resolved synoptic circulation governs precipitation. All models generally reproduce the precipitation-versus-intensity spectrum seen in observations well, with a small tendency toward producing overly strong precipitation at high-intensity thresholds, such as the 95th, 99th, and 99.5th percentiles. Further analysis focuses on precipitation events exceeding the 99.5th percentile that occur simultaneously at several points in the region, yielding so-called “widespread events.” Examination of additional fields shows that the models produce very heavy precipitation events for the same physical conditions seen in the observations.

Download Full-text